Fixing the Broken Model: Look Inside Your Company

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You know that ominous figure people always talk about, that one staggering number—$1.3 billion these days—that represents the cost to develop and market a drug? It is, to be sure, way too high and unsustainably so.

The billions of dollars that have been invested to discover the next generation of blockbusters have, for the most part, failed to bear fruit. In 2009, the industry spent some $65 billion in R&D. That same year 34 new drugs and biologics were approved. Even if one considers that the 2009 drugs were developed in the 10 years prior, the numbers are telling since the industry was spending some $26 billion a year in R&D in 2000. Divide that by 34 and the very crude, very unscientific allocation per drug is some $765 million.

Math games aside, the point is that everyone in the industry recognizes things just can’t go on this way. I’ve lost count of the number of times I have heard a very senior biotech and pharmaceutical executive admit that “the model is broken.” There is a lot of blame to go around: executives bemoan investors’ reluctance to fund their companies while companies, and investors, complain the FDA has become too unpredictable and is not approving drugs at the rate it used to. The growing sense of futility is having a chilling effect on the whole ecosystem of drug discovery.

Often, the $1.3 billion figure is used to illustrate how hard the business is and to help justify the large investment incurred to make drugs. That’s because the figure takes into account not just the one success but all the failures. For each FDA approval there is, on average, one Phase III failure and many more drugs in preclinical and early human tests that don’t make it. All that money spent and lost is clumped together with the money that was invested in the one success.

But a failure is a failure is a failure. The scenario often portrayed to the public is that there are hundreds of drug candidates whose promise dwindles as studies progress, simply because it is discovered that, sadly, they just don’t work as initially thought. This is certainly true of many drug candidates, but not all. A lot of drugs that might actually have made it die because of decisions poorly made, or human error.

Inexperience can play a major role when it comes to these failures, and the biotechnology industry, by virtue of being comprised of so many small, new companies, is especially vulnerable to that. One 2008 analysis published in Nature Reviews Drug Discovery found that 95% of the industry’s Phase III failures in 2006 and 2007 were products originating from biotechnology companies. During the period analyzed in the article, 65 drugs seeking approval experienced regulatory setbacks and 16 of those had 3-month delays. The vast majority of products with delays came from biotech companies. The authors ventured that “many of these delays may have resulted from poor quality NDA submissions, rather than from flaws in the drugs themselves.”

Sounds like a harsh assessment, but it appears as though it’s fairly accurate, at least based on a conversation I recently had with Greg Dombal, managing partner at Halloran Consulting Group, which helps life sciences companies with regulatory and quality assurance issues. I met Dombal last week, at the dinner to kick-off Xconomy’s XSITE summit, and some of the things he said were truly surprising. He says, for example, that about three quarters of the life sciences companies his group sees “have some fundamental gaps in competence.” In a “solid” 30-40 percent, he says, some of the issues can be found at the “C level”—meaning the chief executive, chief operating officer, and other top executives.

Dombal, who’s had extensive experience in regulatory affairs at various companies, later gave me more examples during a phone conversation. One was of a company that did not appropriately forecast expenses in a clinical trial. So the firm ran out of money mid-trial. The problem, says Dombal, was that the company had planned on paying for clinical trials the same way one pays for a construction project, i.e., upon completion of major phases. But that’s not usually the case. If a clinical site delivers data on two patients, it wants payment for those two, Dombal says. “So you do not have the ability to accrue costs for the long term,” and this particular company’s plan did not reflect that, he says. People inside the company overseeing the trial understood how these payments worked, but they apparently were never asked for their input, he says. The company ran out of cash and liquidated all of its assets. It is sad to see, says Dombal, how the inability to ask the right questions inside a company can have such detrimental results—all the money and effort that went into developing this drug candidate is gone.

Another shocking example is that of a company that was finishing a large Phase III clinical trial and was getting ready to submit it for approval to the FDA. The company approached Halloran seeking help with putting together the FDA dossier. That’s when Halloran discovered that two of the company’s vendors—one in the clinical space and one in the manufacturing space—had severe issues. “One didn’t even have a quality system at all, no documentation,” Dombal says. The realization came after Halloran visited the vendors—something the company had not done. If the FDA visited the facilities, they would never pass muster, so Halloran had to break the bad news to the company: in its view, the NDA should not be filed. Essentially, the company has to start all over again. It has to manufacture the drug at a different facility and repeat big portions of its clinical program. “We’re talking tens of millions of dollars that are now lost,” Dombal says. “These are things that you would think could possibly never happen in our industry, and yet they do.”

One last example Dombal gave me was of a company with a combination product—a combo of a drug and a device—that failed to request designation from the FDA as to whether its product should be approved primarily as a drug or a device. The process is straightforward, says Dombal, consisting of an 8- to 10-page summary in which the company asks the agency to review its product through either the office that regulates devices or drugs, with supporting input from the remaining office. Because the company skipped that step, the product ended up in a division that wasn’t the best fit, Dombal says. Questions from the agency came up, and the product is now on clinical hold. “Does the product warrant clinical hold? Absolutely not,” says Dombal. “Did they make a tactical mistake? Yes. They assumed that FDA would understand the technology and did not ensure the right people were involved in the review.” The company is now working to set up a meeting with FDA to resolve the issue, and that effort has cost them nearly 3 months and $65,000.

All these anecdotes make me wonder: what would the $1.3 billion figure look like if one eliminated all failures due to human error, or incompetence, and only counted the unfortunate cases of failures from drugs that just weren’t efficacious enough, no matter how hard the company tried? Maybe that’s the number everyone should strive for.

Sylvia Pagán Westphal is Xconomy's life sciences columnist. You can reach her at swestphal@xconomy.com or you can follow her on Twitter at http://twitter.com/sylviawestphal. Visit http://www.xconomy.com/author/swestphal/ for Sylvia's full bio and disclosures. Follow @

Interesting story. Kwo, to answer your question: corporate advancement is not directly linked to performance. Political skills, sucking-up, manipulative-ness play a bigger role. For example, my own biotech company, nanoString’s CEO for the last year-plus does not even come from the industry. As a company accountant he covered for one of the Directors in a shareholder demand and was promoted to CEO, and has been able to stay for long time, even though he is completely clueless, to the detriment of the company…

I’ve seen organizations focusing and spending money on polishing their office politics skills (called “buzz”) rather than on analytics that would drive efficiencies.

The other piece of the equation is the industry’s insistence on continuing to pursue complex diseases as if they were monogenic in nature. True disease understanding (i.e., root cause analysis) will only begin when medicine links the molecular, the systems (e.g., genomic, proteomic, metabolimic, epigenomic, etc.), and the organism in a holistic approach. Once we do that we will understand that in order to impact disease, we will need to modulate (up and/or down) multiple pathways simultaneously. Instead we pick one pathway, ignore all others, and dose so high that we are guaranteed to see toxic effects with little or no efficacy.